The Research On Project Schedule Control Methods Based On Buffer Management

In today's highly competitive and rapidly changing marketplace, projects are increasingly faced with various uncertainties and risks that may lead to numerous schedule disruptions. Meanwhile, the structure and scale of contempory projects are becoming more and more complex, and the competition on limited resources is aggravating gradually, resulting in an increasing number of projects failing to meet completion deadlines. Traditional project schedule management methods, namely the Critical Path Method (CPM) and the Program Evaluation and Review Technique (PERT), can no longer meet the diversified needs of modern projects. To address these challenges, Goldratt applied the Theory of Constraints (TOC) to the Project Management area and introduced the Critical Chain Scheduling and Buffer Management (CC/BM) methodology. Since its advent, CC/BM has been extensively explored in the academic world and has found its way towards practical applications in the production, manufacturing and service industries, etc. CC/BM relies on deterministic scheduling techniques in order to build a resource feasible schedule that is made robust by inserting centralized time buffers for coping with uncertainty, and improves the schedule performance during project execution to meet the deadline through buffer monitoring. Consequently, the size of buffers and how they are monitored directly determine the project completion time as well as the schedule risk, and hence play crucial role in the successful application of CC/BM. Based on the synthetical application of risk management, project schedule management, robust project scheduling methods, Bayesian Networks, resource flow networks, Monte Carlo simulation methods and heuristic algorithms, this paper performs a systematic study of buffer management-based project scheduling and control methods. The main research contents are outlined as follows:To begin with, a new buffer management framework that takes into consideration the activity duration risk as well as the multi-resource constraint risk is presented. First of all, the key risk factors are identified and their impacts on activity durations are assessed using Bayesian Networks. Next, by the integration of activity resource requirements and the degree of resource constraints that is measured using the resource flow networks, we propose a Resource Risk Index calculation method. Considering these two types of risk, a reasonable buffer sizing approach is developed for the construction of a stable critical chain scheduling plan. And then a dynamic buffer monitoring model is projected that relies on sourcing and transfer of risk based on Bayesian Networks as well as update of resource flow networks. A numerical example validates the effectiveness and practicability of the proposed buffer sizing method.Secondly, the current buffer monitoring mechanism faces a problem of neglecting the dynamic feature of the project execution and related activity information when taking corrective actions. Concerning this issue, we combine buffer monitoring with the activity-based schedule risk analysis (SRA) method, and propose a comprehensive project schedule control framework by introducing the activity cruciality index (CRI) as a trigger for effective expediting to be integrated into the buffer monitoring process. Furthermore, dynamic CRI action threshold settings that depend on the project progress as well as the buffer penetration are presented and examined in order to exhibit a more accurate control system. Our computational experiment demonstrates the superiority of the integrated schedule control methods compared to the predominant buffer monitoring approach, especially when the increasing buffer trigger point is combined with decreasing sensitivity action threshold values.Thirdly, in view of the defect that the most current buffer management practice does not account for the cost information when taking expediting actions, we introduce a new buffer control procedure. In order to explicitly describe the expediting problem within the CC/BM framework, we first present a mathematical optimization model. Given the application limitations of the optimization method, a Monte Carlo simulation-based heuristic approach is then proposed that evaluates the probability of successful project completion relative to the cost of crashing and that determines when to expedite which activities in a cost-effective manner. This approach allows project managers to exploit information concerning buffer penetration and expected probabilistic benefits to generate a candidate set of activities for future expediting as well as to calculate to what extent activity durations should be shortened. Results of an experimental application of the proposed method present its relative dominance over the currently widely adopted buffer management approach with respect to the project time and cost performance.Finally, we study the BM-based project schedule control problem from the perspectives of resource availability constraint and reactive scheduling, and propose a two-phase framework which allows additional resource allocation/reallocation to bring forward activity starting times based on resource cost and schedule stability criteria. In the planning phase, the regular resource availability period is determined based on expected resource cost by simulation optimization. At each decision epoch during the execution phase, an activity that benefits the most from additional resource is selected and the schedule is repaired whenever delays are beyond a certain buffer threshold. These ideas are demonstrated through an example and the factors that have impact on their performance are analyzed through simulation experiments.